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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=358959&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-358959
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ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------
Author: ASF GitHub Bot
Created on: 12/Dec/19 21:55
Start Date: 12/Dec/19 21:55
Worklog Time Spent: 10m
Work Description: KevinGG commented on pull request #10368: [BEAM-8335]
Modify PipelineInstrument to add TestStream for unbounded PCollections
URL: https://github.com/apache/beam/pull/10368#discussion_r357390978
##########
File path: sdks/python/apache_beam/runners/interactive/pipeline_instrument.py
##########
@@ -375,12 +377,15 @@ def _read_cache(self, pipeline, pcoll):
# Can only read from cache when the cache with expected key exists.
if self._cache_manager.exists('full', key):
if key not in self._cached_pcoll_read:
+ if pcoll.is_bounded:
+ read_transform = cache.ReadCache(self._cache_manager, key)
+ else:
+ read_transform = streaming_cache.StreamingCacheReceiver()
Review comment:
This boundedness is implemented 4 months ago in this PR:
https://github.com/apache/beam/commit/79d4bf28c78ba8b7e9a0d01f6c86db79868312b9
Before, Python SDK doesn't care about the boundedness of pvalue instances.
It simply checks the boundedness of io source and pass along the
information:
https://github.com/apache/beam/commit/79d4bf28c78ba8b7e9a0d01f6c86db79868312b9#diff-5bdf3a832591550d5839cb5f76ea2f10R884
So it cannot be source of truth for checking PCollection boundedness.
This can be another motivation for us to unify the 2 caching managers.
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Issue Time Tracking
-------------------
Worklog Id: (was: 358959)
Time Spent: 44h 40m (was: 44.5h)
> Add streaming support to Interactive Beam
> -----------------------------------------
>
> Key: BEAM-8335
> URL: https://issues.apache.org/jira/browse/BEAM-8335
> Project: Beam
> Issue Type: Improvement
> Components: runner-py-interactive
> Reporter: Sam Rohde
> Assignee: Sam Rohde
> Priority: Major
> Time Spent: 44h 40m
> Remaining Estimate: 0h
>
> This issue tracks the work items to introduce streaming support to the
> Interactive Beam experience. This will allow users to:
> * Write and run a streaming job in IPython
> * Automatically cache records from unbounded sources
> * Add a replay experience that replays all cached records to simulate the
> original pipeline execution
> * Add controls to play/pause/stop/step individual elements from the cached
> records
> * Add ability to inspect/visualize unbounded PCollections
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